mapCountryData: Map country-level data.

View source: R/mapCountryData.R

mapCountryDataR Documentation

Map country-level data.

Description

Draw a map of country-level data, allowing countries to be coloured, from an object created in joinCountryData2Map.

Usage

mapCountryData(
  mapToPlot = "",
  nameColumnToPlot = "",
  numCats = 7,
  xlim = NA,
  ylim = NA,
  mapRegion = "world",
  catMethod = "quantiles",
  colourPalette = "heat",
  addLegend = TRUE,
  borderCol = "grey",
  mapTitle = "columnName",
  oceanCol = NA,
  aspect = 1,
  missingCountryCol = NA,
  add = FALSE,
  nameColumnToHatch = "",
  lwd = 0.5
)

Arguments

mapToPlot

a spatial polygons dataframe from joinCountryData2Map() containing country polygons and data, if none specified an internal example data is used

nameColumnToPlot

name of column containing the data you want to plot

numCats

number of categories to put the data in, may be modified if this number is incompatible with the catMethod chosen

xlim

map extents c(west,east), can be overidden by mapRegion

ylim

map extents c(south,north), can be overidden by mapRegion

mapRegion

a country name from getMap()[['NAME']] or 'world','africa','oceania','eurasia','uk' sets map extents, overrides xlim,ylim

catMethod

method for categorisation of data :

  1. "categorical" - each unique value is treated as a separate category

  2. for numeric data : "pretty", "fixedWidth", "diverging", "logFixedWidth", "quantiles"

  3. a numeric vector defining breaks e.g. c(0:5), note that a value of 2 goes into 1-2 not 2-3, uses cut(include.lowest=TRUE)

colourPalette

string describing the colour palette to use, choice of:

  1. "palette" for the current palette

  2. a vector of valid colours, e.g. =c('red','white','blue') or output from RColourBrewer

  3. one of "heat", "diverging", "white2Black", "black2White", "topo", "rainbow", "terrain", "negpos8", "negpos9"

addLegend

whether to add a legend or not

borderCol

the colour for country borders

mapTitle

title to add to the map, any string or 'columnName' to set it to the name of the data column

oceanCol

a colour for the ocean

aspect

aspect for the map, defaults to 1, if set to 'variable' uses same method as plot.Spatial in sp

missingCountryCol

a colour for missing countries

add

whether to add this map on top of an existing map, TRUE/FALSE

nameColumnToHatch

allows hatching of country fills (e.g. to represent uncertainty) , specify a column containing numeric data , highest values will be solid and lower values will have a decreasing density of hatching , new feature more documentation will be added soon

lwd

line width for country borders

Details

Certain catMethod and colourPalette options go well together. e.g. "diverging" and "diverging", "categorical" and "rainbow"

There are two styles of legend available. If catMethod='categorical' or the packages fields and spam are not installed a simple legend with coloured boxes is created. Otherwise a colour bar legend is created. Finer control can be achieved by addMapLegendBoxes or addMapLegend repectively.

Value

invisibly returns a list containing the data and main options used for the map, the list can be passed to addMapLegend or addMapLegendBoxes along with additional options to allow greater flexibility in legend creation.

Warning

will generate unhelpful errors in data categorisation if inappropriate options are chosen, e.g. with catMethod:Quantiles if numCats too high so that unique breaks cannot be defined.

Author(s)

andy south

See Also

classInt, RColorBrewer

Examples


mapCountryData()
data("countryExData",envir=environment(),package="rworldmap")
sPDF <- joinCountryData2Map(countryExData
              , joinCode = "ISO3"
              , nameJoinColumn = "ISO3V10"
              )
mapCountryData( sPDF
              , nameColumnToPlot="BIODIVERSITY" 
              )
              
#user defined map colour scheme for categorical data              
mapParams <- mapCountryData(nameColumnToPlot='GEO3major'
              , catMethod='categorical'
              , addLegend='FALSE'
              , colourPalette=c('white','green','red','yellow','blue','black') 
              )
#changing legendText
mapParams$legendText <- c('antarctic','africa','oceania'
                         ,'americas','s.asia','eurasia')              
do.call( addMapLegendBoxes, c(mapParams,x='bottom',title="Region",horiz=TRUE))

##showing how rworldmap can be used with the classInt and RColorBrewer packages
library(classInt)
library(RColorBrewer)
#getting example data and joining to a map
data("countryExData",envir=environment(),package="rworldmap")
sPDF <- joinCountryData2Map(countryExData,joinCode = "ISO3"
                           ,nameJoinColumn = "ISO3V10")
#getting class intervals using a 'jenks' classification in classInt package
classInt <- classIntervals( sPDF$EPI, n=5, style="jenks")
catMethod = classInt$brks
#getting a colour scheme from the RColorBrewer package
colourPalette <- brewer.pal(5,'RdPu')
#calling mapCountryData with the parameters from classInt and RColorBrewer
mapParams <- mapCountryData( sPDF, nameColumnToPlot="EPI", addLegend=FALSE
                           , catMethod = catMethod, colourPalette=colourPalette )
do.call(addMapLegend, c(mapParams
                       ,legendLabels="all"
                       ,legendWidth=0.5
                       ,legendIntervals="data"))

              



rworldmap documentation built on Oct. 16, 2023, 5:07 p.m.